Past Events

This panel will introduce some new simple foundational results in the theory of supervised learning. It will also discuss open problems in the theory of learning, including problems specific to neuroscience.

On November 4, 2024, the Quest hosted a day-long event, focussed on recent research in natural intelligence and current topics in AI.

Eran Malach is a research fellow at the Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University, studying learning theory and computational aspects of learning and optimization.

"Learning to Reason": Noah Goodman is a Professor of Psychology and Computer Science at Stanford University. His research surrounds computational models of cognition, cognitive development and social cognition, and probabilistic programming languages.

Lorenzo Rosasco is an associate professor at the University of Genoa. His research is focused on theory and algorithms for machine learning.

"Conveying Tasks to Computers: How Machine Learning Can Help" Michael L. Littman, Ph.D. is a Professor of Computer Science at Brown University and Division Director of Infomation and Intelligent Systems at the National Science Foundation.

This research mission broadly aims to understand how children grasp new concepts from few examples, how children build upon layers of concepts to reach an understanding of the world and have the flexibility to solve an unbounded range of problems. Can we build AI that starts like a baby and learns like a child?

The goal of building machines that can perceive and act in the world as humans and other animals do has been a focus of AI research efforts for over half a century. Over this same period, neuroscience has sought to achieve a mechanistic understanding of the brain processes underlying perception and action. It stands to reason that these parallel efforts could inform one another. However recent advances in deep learning and transformers have, for the most part, not translated into new neuroscientific insights; and other than deriving loose inspiration from neuroscience, AI has mostly pursued its own course which now deviates strongly from the brain.